Description
The OpenVINO toolkit is a powerful developer tool that enables developers to create multiplatform computer vision solutions with ease. With this toolkit, developers can build and train AI models in the cloud using popular frameworks such as TensorFlow, MXNet, and Caffe. Once trained, these models can be deployed across a broad range of products.
The OpenVINO toolkit is based on convolutional neural networks (CNN), which are a type of deep learning algorithm that has been proven to be highly effective in image recognition tasks. The toolkit includes a library of functions and preoptimized kernels that enable CNN-based deep learning inference at the edge. This means that the software can perform complex image recognition tasks on devices with limited processing power.
In addition to its support for CNN-based deep learning inference, the OpenVINO toolkit also includes optimized calls for both OpenCV and OpenVX. These libraries provide additional functionality for computer vision applications such as object detection and tracking.
One of the key features of the OpenVINO toolkit is its support for heterogeneous execution across computer vision accelerators. This means that developers can use a common API to deploy their AI models across different hardware platforms including CPU, GPU, Intel Movidius Neural Compute Stick, and FPGA.
The ability to deploy AI models across different hardware platforms is particularly important in today's world where there are many different types of devices with varying levels of processing power. By using the same API across all these devices, developers can ensure that their applications will work seamlessly regardless of which device they are running on.
Another advantage of using the OpenVINO toolkit is its ease-of-use. The software comes with comprehensive documentation and tutorials that make it easy for even novice developers to get started quickly. Additionally, there are many online resources available including forums where users can ask questions or share tips and tricks.
Overall, if you're looking for a powerful developer tool for creating multiplatform computer vision solutions then look no further than the OpenVINO toolkit! With its support for popular frameworks like TensorFlow and MXNet along with optimized calls for both OpenCV and OpenVX plus heterogeneous execution across multiple hardware platforms - this software has everything you need to get started building cutting-edge AI applications today!
Full spec
| Publisher | Intel Software |
| Publisher site | http://www.intel.com/software/products |
| Release date | 2018-07-23 |
| Date added | 2018-07-23 |
| Category | Developer Tools |
| Sub category | Programming Software |
| Version | 2018 |
| Os requirements | Windows, Windows 7, Windows 8, Windows 10 |
| Requirements | None |
| Price | Free |
| Downloads per week | 0 |
| Total downloads | 67 |
Comments:
This OpenVINO toolkit is amazing! It has greatly optimized my deep learning models on Windows.
I completely agree, Peter! The performance improvements are remarkable.
I've been using OpenVINO for image classification tasks, and it has been a game-changer. Highly recommended.
Does OpenVINO support all major deep learning frameworks?
Yes, Lisa! OpenVINO supports popular frameworks like TensorFlow and Caffe.
I've noticed significant speed improvements when using OpenVINO with TensorFlow models.
OpenVINO's compatibility with multiple frameworks is a great advantage. It makes integration much easier.
That's excellent! I'll definitely give it a try for my next deep learning project.
You won't be disappointed, Lisa. OpenVINO simplifies deployment and improves inference performance.
I had some difficulties installing OpenVINO on Windows. Any tips on the installation process?
Hi John! I had a smooth installation experience. Can you provide more details about the difficulties you encountered?
Sure, Michael. I faced issues with the system requirements, specifically regarding the hardware.
Thanks, Sarah and Michael! I'll definitely check out the Intel community forums for OpenVINO support.
Thank you, Sarah and Michael! I'll explore the tutorials and sample codes to gain a better understanding of OpenVINO.
Make sure your hardware meets the OpenVINO requirements. It needs particular CPU and GPU capabilities.
Thanks for the tip, Sarah! I'll double-check the hardware requirements before attempting the installation again.
Can OpenVINO be used for real-time video analytics?
Absolutely, Lisa! OpenVINO provides powerful features for real-time video analysis, including object detection and tracking.
I'm glad to hear that! Real-time video analytics is crucial for my project.
OpenVINO's performance optimizations will be very beneficial for real-time video analytics, John.
OpenVINO's multi-threading capabilities can significantly accelerate video processing tasks.
That's exactly what I need for my video surveillance application. OpenVINO seems to be the right choice.
I've used OpenVINO for video surveillance projects, and it works like a charm, Lisa.
Is there any support or community forums available for OpenVINO?
Yes, John! Intel provides official support for OpenVINO, and you can find helpful resources, tutorials, and forums on their website.
Thank you, Peter and Sarah! I'll review the system requirements documentation before proceeding with the installation.
I've also found the Intel community forums to be a great place to ask questions and get assistance related to OpenVINO.
Is the OpenVINO toolkit free to use?
Yes, Lisa! OpenVINO is free to download and use. You can find it on the official Intel website.
It's great to see such a powerful deep learning toolkit available for free. It really democratizes AI development.
Indeed, Sarah! OpenVINO's accessibility plays a significant role in accelerating the development of AI applications.
That's fantastic! OpenVINO's free availability makes it easier for developers to explore AI capabilities.
What are the system requirements for OpenVINO on Windows?
To use OpenVINO on Windows, you need a compatible CPU, GPU, and operating system. Intel provides detailed documentation on their website.
Make sure to check the Intel website for the specific hardware and software requirements of the OpenVINO toolkit on Windows.
OpenVINO's system requirements are essential to ensure optimal performance and compatibility. Good luck, Lisa!
Can OpenVINO be used with Python?
Absolutely, John! OpenVINO provides Python APIs for seamless integration with Python-based deep learning applications.
Python support in OpenVINO makes it easier to leverage the toolkit's capabilities within existing Python workflows.
Using OpenVINO with Python allows for flexible and efficient development of AI applications.
That's fantastic! Python integration will make it much easier for me to work with OpenVINO.
I highly recommend using the OpenVINO Python API, Lisa. It provides a seamless experience.
Are there any tutorials available to get started with OpenVINO on Windows?
Yes, John! Intel has a rich collection of tutorials and sample codes on their website to help you get started quickly.
The tutorials provided by Intel are comprehensive and cover various aspects of OpenVINO usage. They are definitely worth checking out.
Is there a community of developers who actively contribute to OpenVINO?
Yes, Lisa! The OpenVINO community is growing, and developers actively contribute through code contributions, discussions, and feedback.
The active developer community ensures that OpenVINO stays updated, incorporates new features, and addresses issues promptly.
Being a part of the OpenVINO community allows developers to learn and collaborate with like-minded individuals.
That's great to know! Being a part of an active community is always beneficial in the software development world.